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Articles 1 - 8 of 8
Full-Text Articles in Biomedical
Modification Of Time-Domain Terahertz Spectroscopy System To Polarimetry Imaging System With Application To Human Breast Cancer Surgical Specimen, Nikita Gurjar
Graduate Theses and Dissertations
Breast-conserving therapy (lumpectomy) is one of the most performed breast cancer surgeries in the United States. The best outcome of lumpectomy surgery is achieved when the surgical margins are free of cancer. When remnants of cancer are detected at the surgical margins after the initial operation, a second operation will be required to remove the cancer. Unfortunately, a significant number of patients undergo breast conserving surgery (BCS) at local hospitals that do not have access to immediate on-site pathology leading to high rates of re-excision or reoperation (greater than 30%). Therefore, there is a significant need for new intraoperative technology …
Special Section Editorial: Artificial Intelligence For Medical Imaging In Clinical Practice, Claudia Mello-Thoms, Karen Drukker, Sian Taylor-Phillips, Khan Iftekharuddin, Marios Gavrielides
Special Section Editorial: Artificial Intelligence For Medical Imaging In Clinical Practice, Claudia Mello-Thoms, Karen Drukker, Sian Taylor-Phillips, Khan Iftekharuddin, Marios Gavrielides
Electrical & Computer Engineering Faculty Publications
This editorial introduces the JMI Special Section on Artificial Intelligence for Medical Imaging in Clinical Practice.
Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche
Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche
Electronic Theses and Dissertations
The recent rise of big data technology surrounding the electronic systems and developed toolkits gave birth to new promises for Artificial Intelligence (AI). With the continuous use of data-centric systems and machines in our lives, such as social media, surveys, emails, reports, etc., there is no doubt that data has gained the center of attention by scientists and motivated them to provide more decision-making and operational support systems across multiple domains. With the recent breakthroughs in artificial intelligence, the use of machine learning and deep learning models have achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous …
Evaluation Of Terahertz Imaging For Breast Cancer Detection Using Image Morphing, Tanny Andrea Chavez Esparza
Evaluation Of Terahertz Imaging For Breast Cancer Detection Using Image Morphing, Tanny Andrea Chavez Esparza
Graduate Theses and Dissertations
This thesis proposes the use of a mesh morphing algorithm for the quantitative evaluation of terahertz (THz) images. This work differs from traditional evaluation methods based on qualitative evaluation because it provides a fair and quantitative measurement of the THz imaging system's performance. The objective of the algorithm is to match the alignment, shape, and resolution of the THz and reference pathology images. Therefore, the proposed morphing method provides a pathology reference for a pixel-by-pixel evaluation of the region classification in the THz image. To achieve this, the morphing algorithm aligns the images using the Pearson's correlation coefficient and reshapes …
3d Bioprinting Systems For The Study Of Mammary Development And Tumorigenesis, John Reid
3d Bioprinting Systems For The Study Of Mammary Development And Tumorigenesis, John Reid
Electrical & Computer Engineering Theses & Dissertations
Understanding the microenvironmental factors that control cell function, differentiation, and stem cell renewal represent the forefront of developmental and cancer biology. To accurately recreate and model these dynamic interactions in vitro requires both precision-controlled deposition of multiple cell types and well-defined three-dimensional (3D) extracellular matrix (ECM). To achieve this goal, we hypothesized that accessible bioprinting technology would eliminate the experimental inconsistency and random cell-organoid formation associated with manual cell-matrix embedding techniques commonly used for 3D, in vitro cell cultures. The first objective of this study was to adapt a commercially-available, 3D printer into a 3D bioprinter. Goal-based computer simulations were …
Breast Cancer Classification Of Mammographic Masses Using Circularity Max Metric, A New Method, Tae Keun Heo
Breast Cancer Classification Of Mammographic Masses Using Circularity Max Metric, A New Method, Tae Keun Heo
Electronic Theses and Dissertations
Breast cancer classification can be divided into two categories. The first category is a benign tumor, and the other is a malignant tumor. The main purpose of breast cancer classification is to classify abnormalities into benign or malignant classes and thus help physicians with further analysis by minimizing potential errors that can be made by fatigued or inexperienced physicians. This paper proposes a new shape metric based on the area ratio of a circle to classify mammographic images into benign and malignant class. Support Vector Machine is used as a machine learning tool for training and classification purposes. The improved …
Enhanced Diagnostic Accuracy Of Mammograms On A Mobile Device, Sharanya Padmanabhan
Enhanced Diagnostic Accuracy Of Mammograms On A Mobile Device, Sharanya Padmanabhan
Open Access Theses
With the death of a woman every 13 minutes in the US, and one every minute worldwide, due to breast cancer, the need for early detection cannot be overstated. Mammography is a boon for both early detection and screening of breast tumors. It is an imaging system that uses low dose (9mrem) x-rays for examining the breasts, by the electrons reflected from the tissues (thermoelectric effect). However, there are 20% false positives and 10% false negatives in current practice. Hence, there is a critical need for enhancing the accuracy of these mammograms. Towards this, this thesis was aimed at enhancing …
Radio-Frequency Breast Cancer Imaging Results For A Simplified Cylindrical Phantom, Giuseppe Ruvio, Raffaele Solimene, Antonietta D'Alterio, Max Ammann, Rocco Pierri
Radio-Frequency Breast Cancer Imaging Results For A Simplified Cylindrical Phantom, Giuseppe Ruvio, Raffaele Solimene, Antonietta D'Alterio, Max Ammann, Rocco Pierri
Conference Papers
Microwave imaging is a pervasive research field and
is useful in numerous applicative diagnostic noninvasive contexts. This paper focuses on two aspects. First, we perform a numerical investigation to assess the role played by fundamental parameters (i.e. number of sensors, operating frequency bandwidth) on cancer detection. To this end, a simplified cylindrical phantom probed by ideal two-dimensional dipoles (i.e. infinitely long along the axis of invariance) is considered. Second, in order to focus on the role of the antennas, we analyze, still by numerical simulations and for a simplified breast model, how performances vary when a realistic antenna is adopted.